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Expert tutoring and natural language...
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Lu, Xin.
Expert tutoring and natural language feedback in intelligent tutoring systems.
紀錄類型:
書目-電子資源 : 單行本
正題名/作者:
Expert tutoring and natural language feedback in intelligent tutoring systems./
作者:
Lu, Xin.
面頁冊數:
142 p.
附註:
Source: Dissertation Abstracts International, Volume: 68-07, Section: B, page: 4598.
Contained By:
Dissertation Abstracts International68-07B.
標題:
Computer Science. -
電子資源:
Download PDF (下載PDF全文)
ISBN:
9780549147794
Expert tutoring and natural language feedback in intelligent tutoring systems.
Lu, Xin.
Expert tutoring and natural language feedback in intelligent tutoring systems.
- 142 p.
Source: Dissertation Abstracts International, Volume: 68-07, Section: B, page: 4598.
Thesis (Ph.D.)--University of Illinois at Chicago, 2007.
Intelligent tutoring systems can provide benefits of one-on-one instruction automatically and cost effectively. To make the intelligent tutoring systems as effective as expert human tutors, the utility of a computational model of expert tutoring in generating effective natural language feedback in intelligent tutoring systems is demonstrated.
ISBN: 9780549147794Subjects--Topical Terms:
1000005419
Computer Science.
Expert tutoring and natural language feedback in intelligent tutoring systems.
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Source: Dissertation Abstracts International, Volume: 68-07, Section: B, page: 4598.
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Adviser: Barbara Di Eugenio.
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Thesis (Ph.D.)--University of Illinois at Chicago, 2007.
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Intelligent tutoring systems can provide benefits of one-on-one instruction automatically and cost effectively. To make the intelligent tutoring systems as effective as expert human tutors, the utility of a computational model of expert tutoring in generating effective natural language feedback in intelligent tutoring systems is demonstrated.
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To set up a basis for computationally modeling expert tutoring, a comprehensive study of the difference between one expert tutor and two non-expert tutors in effectiveness, behavior and language is presented. Based on the empirical results, a rule-based model of expert tutoring is developed, which takes advantage of a machine learning technique, Classification based on Associations. To employ the model of expert tutoring in the natural language feedback generation for intelligent tutoring systems, a framework of feedback generation with 3-tier probabilistic planning is designed. The 3-tier planning automatically generates, selects and monitors plans for generating effective tutorial feedback based on the rule-based model and the information state which keeps track of the interaction in the intelligent tutoring system. The evaluation results show that the tutorial rules successfully model expert tutoring and the intelligent tutoring system using them improves learning significantly.
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Download PDF (下載PDF全文)
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